Search

Purpose: To evaluate the impact of video sequences (cine-loops) on the interobserver agreement (IOA) using risk stratification systems (RSSs) for thyroid nodules (TNs). Methods: Twenty TNs were randomly selected from a large database and evaluated by twelve experienced observers using five different RSSs (Kwak-, ACR-, EU-, Korean-TIRADS, ATA Guidelines). In the first step, the evaluation was conducted based on static ultrasound (US) images in two planes (“static”). Six months later, these cases were reevaluated by the same observers using video sequences in two planes (“cine-loops”). Fleiss’ kappa (κ) was calculated for the IOA analyses. Results: IOA on static was moderate with κ values of 0.46, 0.42, 0.40, 0.45, and 0.38 for the Kwak-, ACR-, EU-, Korean-TIRADS, and ATA Guidelines, respectively, while the IOA on cine-loops was fair with κ values of 0.41, 0.38, 0.37, 0.36, and 0.34 for the Kwak-, ACR-, EU-, Korean-TIRADS, and ATA Guidelines, respectively. The overall IOA was superior in static images versus cine-loops (p = 0.024). Among other findings, the subgroup analyses (related to age, gender, US certificates, number of thyroid US per week, and RSSs experience) particularly showed that the experience of the observers in using RSSs had a significant influence on the IOA. Conclusions: The overall IOA (all twelve observers and all five RSSs) was superior on static US images in comparison to cine-loops. Furthermore, the overall IOA of the five US features revealed superior κ values of the static images over cine-loops. However, this impact was significantly lower when the observers were highly experienced in the use of US RSSs of TNs.

Background: Thyroid nodules are very common. In most cases, they are benign, but they can be malignant in a low percentage of cases. The accurate assessment of these nodules is critical to choosing the next diagnostic steps and potential treatment. Ultrasound (US) imaging, the primary modality for assessing these nodules, can lack objectivity due to varying expertise among physicians. This leads to observer variability, potentially affecting patient outcomes. Purpose: This study aims to assess the potential of a Decision Support System (DSS) in reducing these variabilities for thyroid nodule detection and region estimation using US images, particularly in lesser experienced physicians. Methods: Three physicians with varying levels of experience evaluated thyroid nodules on US images, focusing on nodule detection and estimating cystic and solid regions. The outcomes were compared to those obtained from a DSS for comparison. Metrics such as classification match percentage and variance percentage were used to quantify differences. Results: Notable disparities exist between physician evaluations and the DSS assessments: the overall classification match percentage was just 19.2%. Individually, Physicians 1, 2, and 3 had match percentages of 57.6%, 42.3%, and 46.1% with the DSS, respectively. Variances in assessments highlight the subjectivity and observer variability based on physician experience levels. Conclusions: The evident variability among physician evaluations underscores the need for supplementary decision-making tools. Given its consistency, the CAD offers potential as a reliable “second opinion” tool, minimizing human-induced variabilities in the critical diagnostic process of thyroid nodules using US images. Future integration of such systems could bolster diagnostic precision and improve patient outcomes.

Purpose: To compare the diagnostic performance of thyroid imaging reporting and data system (TIRADS) in combination with shear wave elastography (SWE) for the assessment of thyroid nodules. Methods: A prospective study was conducted with the following inclusion criteria: preoperative B-mode ultrasound (US) including TIRADS classification (Kwak-TIRADS, EU-TIRADS), quantitative SWE and available histological results. Results: Out of 43 patients, 61 thyroid nodules were detected; 10 nodules were found to be thyroid cancer (7 PTC, 1 FTC, 2 HüCC) and 51 were benign. According to Kwak-TIRADS the majority of benign nodules (47 out of 51, 92.2%) were classified in the low-risk- and intermediate-risk class, four nodules were classified as high-risk (7.8%). When using EU-TIRADS, the benign nodules were distributed almost equally across all risk classes, 21 (41.2%) nodules were classified in the low-risk class, 16 (31.4%) in the intermediate-risk class and 14 (27.4%) in the high-risk class. In contrast, most of the malignant nodules (eight out of ten) were classified as high-risk on EU-TIRADS. One carcinoma was classified as low-risk and one as intermediate-risk nodule. For SWE, ROC analysis showed an optimal cutoff of 18.5 kPa to distinguish malignant and benign nodules (sensitivity 80.0%, specificity 49.0%, PPV 23.5% and NPV 92.6%). The addition of elastography resulted in an increase of accuracy from 65.6% to 82.0% when using Kwak-TIRADS and from 49.2% to 72.1% when using EU-TIRADS. Conclusion: Our data demonstrate that the combination of TIRADS and SWE seems to be superior for the risk stratification of thyroid nodules than each method by itself. However, verification of these results in a larger patient population is mandatory.